Extraction of a dynamic structure of biological signals as stochastic automata for a human-machine interface

Concerning a human-machine interface, we investigate a method to extract the dynamical structure from biological signals. Applying the ε-Machine reconstruction technique to the measured time series of the pulsation of a human finger´s capillary vessels, we extract the macroscopic structure of its dynamics using a stochastic automaton. In terms of stochastic automata, we evaluate the graph complexity and the identification performance of the constructed automaton. To measure the pulsation of a capillary vessel, we use a reflection type pick-up consisting of an infrared sensor unit and an infrared emitter